Code written by AI is really poorly written. A couple smells I’ve noticed:
On the other hand, if you’re in a green field project and need to throw up some simple, dirty CSS/HTML for a quick marketing page, sure, let the AI bang it out. Some projects don’t need to be done well, they just need to be done fast.
And the autocomplete features can be a time saver in some cases regardless.
Sounds about right, I had a positive experience when I told my local LLM to refactor a function and add a single argument.
I would not dare letting it loose on a whole source file, because it changes random things giving you more code to review.
In my view current LLM’s do a acceptable job with:
Yeah likewise. I think it shows the primary weakness of Llms right now is not skill or understanding, but context.
It can’t use functions or docs that it doesn’t know about. Neither can I. RAG systems are supposed to solve this but in practice they don’t seem to work that great
It doesn’t reuse code that already exists in the project
I had a pissing contest with one of the junior guys over this. He didn’t seem to understand why we should use the existing function and had learned so little about the code base that he didn’t know where to find it. He’s gone
The more interesting flaw in his ai code was it hallucinated an entirely different mocking tool for unit tests
svtdragon@lemmy.world 1 week ago
I just spent about a month using Claude 3.7 to write a new feature for a big OSS product. The change ended up being about 6k loc with about 14k of tests added to an existing codebase with an existing test framework for reference.
For context I’m a principal-level dev with ~15 years experience.
The key to making it work for me was treating it like a junior dev. That includes priming it (“accuracy is key here; we can’t swallow errors, we need to fail fast where anything could compromise it”) as well as making it explain itself, show architecture diagrams, and reason based on the results.
After every change there’s always a pass of “okay but you’re violating the layered architecture here; let’s refactor that; now tell me what the difference is between these two functions, and shouldn’t we just make the one call the other instead of duplicating? This class is doing too much, we need to decompose this interface.”
In my own personal experience it was actually kinda fun. I’d say it made me about twice as productive.
I would not have said this a month ago. Up until this project, I only had stupid experiences with AI (Gemini, GPT).
pennomi@lemmy.world 1 week ago
Agreed. I use it in my daily workflow but you as the senior developer have to understand what can and cannot be delegated, and how to stop it from doing stupid things.
For instance when I work in computer vision or other math-heavy code, it’s basically useless.
FarceOfWill@infosec.pub 1 week ago
Typically working with a junior on a project is slower than not working with them. It’s a little odd you see this as like that and that it’s also faster.
Quik@infosec.pub 1 week ago
I don’t think it’s odd, because LLMs are just way faster than any junior (or senior) Dev. So it’s more like working with four junior devs but with the benefit of having tasks done sequentially without the additional overhead of having to give tasks to individual juniors and context switching to review their changes.
(Obviously, there are a whole lot of new pitfalls, but there a real benefits in some circumstances)
drspod@lemmy.ml 1 week ago
Link to the patch?
svtdragon@lemmy.world 1 week ago
The PR isn’t public yet (it’s in my fork) but even once I submit it upstream I don’t think I’m ready to out my real identity on Lemmy just yet.